Data Analysis Project Using PostgreSQL and Jupyter Notebook

Created by; @carloscoronatax

Project Overview

This project performs data analysis by connecting PostgreSQL database with Jupyter Notebook. The analysis leverages Python's data manipulation libraries to extract insights from the data stored in a PostgreSQL database.

Note: This project is updating every day, but you can use the fundamentals right now.

Tech Stack

• PostgreSQL: Database management system
• Jupyter Notebook: Interactive computing environment

Setup Instructions

1. Environment Setup

# Install required packages
pip install pandas numpy psycopg2-binary sqlalchemy matplotlib seaborn jupyter

2. Database Connection

# PostgreSQL connection configuration
host = 'localhost'
database = 'postgres'
user = 'postgres'
password = 'your_password'

3. Project Structure

new_project/
├── notebook.ipynb           # Jupyter notebook
└── README.md

Data Analysis Process

1. Data Extraction

• Connect to PostgreSQL database
• Query and load tables into pandas DataFrames
• Initial data inspection

2. Data Cleaning

• Handle missing values
• Remove duplicates
• Format data types
• Standardize values

3. Exploratory Data Analysis (EDA)

• Statistical summaries
• Data distribution analysis
• Correlation analysis
• Trend identification

4. Visualization

• Create charts and graphs
• Generate insights
• Document findings

Usage Example

# Connect to database and load data
engine = create_postgres_connection(
    host='localhost',
    database='postgres',
    user='postgres',
    password='your_password'
)

# Read data into DataFrame
df = read_table_to_dataframe(engine, 'your_table')

# Basic analysis
print("Dataset Shape:", df.shape)
print("\nData Types:\n", df.dtypes)
print("\nSummary Statistics:\n", df.describe())

Data Security

• Keep database credentials secure
• Use environment variables for sensitive information
• Don't commit credentials to version control

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

MIT License

Contact

Created and Maintained by: Carlos Corona

GitHub: @carloscoronatax